Abstract
This
study introduces perceived effectiveness and equity as key dimensions of public
perception of artificial intelligence (AI) and examines racial disparities in
these perceptions. Using
the American Trends Panel survey by Pew Research Center, this study examines
how White, Black, and Asian respondents perceive effectiveness and equity in
AI's application overall and in different fields. Findings show that both Black
and White respondents have a relatively lower level of overall perceived
effectiveness of AI, while Asian respondents have a higher level of
effectiveness perception. For specific fields of AI application, Black
respondents have a lower level of perceived AI’s effectiveness in detecting
cancer and producing crop than the other groups, while White respondents have a
lower level of perceived effectiveness of AI’s application in mental
healthcare, detecting protein structure, and writing news, suggesting Black is
more cautious about AI’s application in fields that are directly related to
resources and personal interests, while White is less optimistic about AI’s
applications in fields that involve more personal components or
personalization. In terms of perceived equity, Black
respondents report a lower level of perceived equity overall, as well on
healthcare and hiring, which goes against previous expectations that AI
contributes to mitigating inequity. This study also examines whether and how
individual characteristics are associated with such perceptions in these racial
groups, as well as find an association between the perceptions and general
attitude toward AI. As AI plays an increasingly important role in our society, these
findings reveal racial disparity in perceived effectiveness and equity of AI,
along with relevant factors. Overall, this study speaks to racial inequity in
the context of technology development, contributes to our understanding of
different racial groups’ preferences and concerns about AI, and calls for a
development of AI that benefits different groups more equally.
